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Cooperative driving of mixed autonomy vehicles: A delay-compensating MPC approach

Fundamental Research 2025年

作者： Wang, Xuan Bian, Yougang Hu, Mangjiang Qin, Hongmao Ding, Rongjun The State Key Laboratory of Advanced Design and Manufacturing Technology for Vehicle College of Mechanical and Vehicle Engineering Hunan University Changsha 410082 China Wuxi Intelligent Control Research Institute (WICRI) of Hunan University Wuxi 214115 China

The era of mixed autonomy when connected automated vehicles and human-driven vehicles co-exist will last a long time. Communication time delays are inevitable and may highly deteriorate the safety and stability of mixed vehicle platoons in dynamic tracking scenarios. To address this challenge, this paper proposes a model predictive control (MPC) method for cooperative control of mixed platoons with time-varying communication delays. The detriments of time delay to cooperative control are analyzed and two delay compensation mechanisms are established, based on which a dual-mode MPC controller is designed. The feasibility, closed-loop stability, and head-to-tail string stability are theoretically proved. Furthermore, numerical simulations are conducted to verify the effectiveness of the proposed MPC controller. Simulation results show that the proposed controller outperforms the state-of-the-art consensus-based controller with 4.5 %-5.8 % fuel consumption reduction and 28.1 %-33.1 % average velocity error reduction. © 2025

关键词： Communication delays Cooperative control Human-driven vehicles Mixed autonomy Model predictive control Vehicle platoon

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On the simulation of expressional animation based on facial MoCap

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Science China(Information Sciences) 2013年第10期56卷 265-276页

作者： FANG XiaoYong WEI XiaoPeng ZHANG Qiang ZHOU ChangJun Key Laboratory of Advanced Design and Intelligent Computing (Dalian University) Ministry of Education School of Management Dalian University of Technology

MoCap(motion capture)-based animation is a hot issue in computer animation research *** on the optical MoCap system,this paper proposes a novel cross-mapping based facial expression simulating *** overcome the problem of the false upper and lower jaw correlation derived from the facial global RBFbased cross-mapping method,we construct a functional partition based RBF cross-mapping *** model animating,enhanced markers are added and animated by our proposed skin motion *** addition,based on the enhanced markers,an improved RBF-based animating approach is raised to derive realistic facial *** more,a pre-computing algorithm is presented to reduce computational cost for real-time *** experiments proved that the method can not only map the MoCap data of one subject to diferent personalized faces but generate realistic facial animation.

关键词： facial animation cross-mapping functional partition motion mechanism RBF

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Comparison study of Gauss, MQ and TPS for interpolation application

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International Journal of Industrial and Systems Engineering 2014年第2期18卷 185-198页

作者： Zhang, Qiang Zheng, Guangguo Zhou, Dongsheng Key Laboratory of Advanced Design and Intelligent Computing Ministry of Education Dalian University Dalian 116622 China

There are mainly two parts in this paper. In the first part, we briefly introduce the basic theory of the radial basis function (RBF) and its application in scattered data interpolation, and investigate the difference among three kernel functions: multi-quadric, Gauss and thin plate spline, in detail. According to the multiple examples, we make a lot of experiments, and develop a system in the C++ programme language and the OpenGL open graphics library to make simulation experiments. Finally, we analyse and summarise the different characteristics of the each kernel function in the process of interpolation. In addition, on the basis of the well-known interpolation theory and the analysis of the experimental data, we list several examples for interpolation comparisons. In the second part, the distance of the current marked points down to its most neighbouring marked points is used as shape parameter. Combining with other shape parameter for analysis and comparisons, the results represent the different influences of RBF shape parameter on the curve and surface construction. Our experiment results obtained in this article have theoretical guide values in graphic interpolation modelling. Copyright © 2014 Inderscience Enterprises Ltd.

关键词： Interpolation

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Scattered data processing approach based on optical facial motion capture

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Applied Bionics and Biomechanics 2013年第2-3期10卷 75-87页

作者： Zhang, Qiang Liang, Xiaoying Wei, Xiaopeng Key Laboratory of Advanced Design and Intelligent Computing Dalian University Ministry of Education Dalian 116622 China

In recent years, animation reconstruction of facial expressions has become a popular research field in computer science and motion capture-based facial expression reconstruction is now emerging in this field. Based on the facial motion data obtained using a passive optical motion capture system, we propose a scattered data processing approach, which aims to solve the common problems of missing data and noise. To recover missing data, given the nonlinear relationships among neighbors with the current missing marker, we propose an improved version of a previous method, where we use the motion of three muscles rather than one to recover the missing data. To reduce the noise, we initially apply preprocessing to eliminate impulsive noise, before our proposed three-order quasi-uniform B-spline-based fitting method is used to reduce the remaining noise. Our experiments showed that the principles that underlie this method are simple and straightforward, and it delivered acceptable precision during reconstruction. © 2013 - IOS Press and the authors. All rights reserved.

关键词： Noise abatement

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Time-varying stiffness analysis on rotating shaft with elliptical-front crack

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International Journal of Industrial and Systems Engineering 2014年第3期17卷 302-314页

作者： Wei, Xiaopeng Liu, Dajun Zhao, Lasheng Zhang, Qiang Key Laboratory of Advanced Design and Intelligent Computing Dalian University Ministry of Education Dalian 116622 China

The aim of this paper is to investigate the difference of time-varying stiffness characteristics between a semi-elliptical front crack and a straight front crack of shaft-element in order to obtain a more accurate and realistic cracked-rotor model for rotating machinery system. By calculating the correct time-varying area moments of inertia for the cross-section of cracked element and taking account the neutral axis position changes, the switching function is obtained, meanwhile the stiffness of shaft in a steady rotating cycle is determined. The result shows that a significant difference of stiffness appears as crack depth deepens. Especially, the difference between elliptical-front (EF) and straight-front (SF) cracked element is more obvious in the early crack propagation. © 2014 Inderscience Enterprises Ltd.

关键词： Cracks

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LarTap: A Luminance-aware Framework with Text-correlation Priors for Multi-Exposure Image Fusion

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IEEE Transactions on Circuits and Systems for Video Technology 2025年

作者： Wang, Enlong Li, Jiawei Yan, Tiantian Lei, Jia Zhou, Shihua Wang, Bin Liu, Jinyuan Kasabov, Nikola K. Dalian University Key Laboratory of Advanced Design and Intelligent Computing Ministry of Education School of Software Engineering Dalian116622 China University of the Science and Technology Beijing School of Computer and Communication Engineering Beijing100083 China Xi’an Jiaotong University School of Software Engineering Shaanxi Xi’an710049 China Dalian Univer sity of Technology School of Mechanical Engineering Dalian116024 China Auckland University of Technology Knowledge Engineering and Discovery Research Institute Auckland1061 New Zealand

Conventional imaging devices often struggle to produce high-dynamic-range (HDR) images that accurately represent natural scenes. To overcome this limitation, multi-exposure image fusion (MEF) techniques have been introduced as a viable solution. Existing MEF approaches aim to enhance performance by optimizing or searching architectures. However, they face challenges in precise feature extraction and scene reconstruction, leading to distortion in the fused images. Additionally, most methods do not adequately address luminance variations across different image regions, which may result in the loss of essential details. To address these challenges, we present a novel luminance-aware MEF framework that integrates text-correlation priors (LarTap). By embedding textual information into fusion process, the proposed framework enhances content extraction and comprehension. Specifically, it consist of two key components: the text-image correlation network (N1) and the multi-exposure fusion network (N2). First, N1 performs correlation training to achieve a holistic alignment between text and image pairs. Its iterative vision encoders (VEs) generate text-correlated prior knowledge to facilitate the fusion process in N2. Second, N2 leverages these priors for scene reconstruction and dynamically adjusts luminance based on comparative perception. Extensive experiments on multiple datasets demonstrate that LarTap outperforms state-of-the-art methods. © 1991-2012 IEEE.

关键词： Image correlation

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A Novel Tunable Stiffness Method Using Gecko Setae-Inspired Adhesive Interlayer Films for Soft Actuator

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Journal of Bionic Engineering 2025年 1-16页

作者： Wang, Zhihuan Xu, Linsen Ye, Liangzhi Wang, Mingming Zhang, Zhihua Wu, Tao College of Mechanical and Electrical Engineering Hohai University Changzhou213000 China Changzhou Key Laboratory of Intelligent Manufacturing Technology and Equipment Changzhou213000 China Suzhou Research Institute Hohai University Suzhou215000 China Changzhou Institute of Advanced Manufacturing Technology Changzhou213000 China Wuhan Second Ship Design and Research Institute Wuhan430000 China

Soft actuators are inherently flexible and compliant, traits that enhance their adaptability to diverse environments and tasks. However, their low structural stiffness can lead to unpredictable and uncontrollable complex deformations when substantial force is required, compromising their load-bearing capacity. This work proposes a novel method that uses gecko setae-inspired adhesives as interlayer films to construct a layer jamming structure to adjust the stiffness of soft actuators. The mechanical behavior of a single tilted microcylinder was analyzed using the energy method to determine the adhesion force of the adhesives. The gecko-inspired adhesive was designed under the guidance of the adhesion force model. Testing under various loads and directions revealed that the tilted characteristic of microcylinders can enhance the adhesion force in its grasping direction. The adhesive demonstrated excellent adhesion performance compared to other typical adhesives. A tunable stiffness actuator using gecko setae-inspired adhesives (TSAGA), was developed with these adhesives serving as interlayer films. The stiffness model of TSAGA was derived by analyzing its axial compression force. The results of stiffness test indicate that the adhesives serve as interlayer films can adjust the stiffness in response to applied load. TSAGA was compared with other typical soft actuators in order to evaluate the stiffness performance, and the results indicate that TSAGA exhibits the highest stiffness and the widest tunable stiffness range. This demonstrates the superior performance of the setae-inspired adhesives as interlayer films in terms of stiffness adjustment. © Jilin University 2025.

关键词： Glues

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Research on Robust Measurement Method of Heart Rate Using Remote Photoplethysmography Based on Adversarial Learning Network with High and Low Frequency Features

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IEEE Transactions on Circuits and Systems for Video Technology 2025年

作者： Zhai, Dezhao Chen, Wei Ding, Yinghao Yu, Ming Li, Qinwei Wu, Hang Tianjin University of Technology Tianjin Key Laboratory for Advanced Mechatronic System Design and Intelligent Control School of Mechanical Engineering Tianjin300384 China National Demonstration Center for Experimental Mechanical and Electrical Engineering Education Tianjin University of Technology China People's Liberation Army Systems Engineering Institute Academy of Military Sciences Tianjin300161 China Civil Aviation University of China Tianjin Key Laboratory for Advanced Signal Processing Tianjin300300 China Nankai University School of Artificial Intelligence Tianjin300381 China

Remote Photoplethysmography (rPPG) is a non-contact method for measuring heart rate (HR) through facial video, breaking the constraints of contact measurements and offering broad application prospects. However, in real monitoring scenarios, the distance of subjects and facial illumination often vary. This leads to degradation of rPPG signals due to changes in facial resolution and light intensity. This paper presents the High and Low Frequency Feature Adversarial Learning Network (HLFF-AL), which utilizes feature space interpolation and composite feature capture to perform multi-band global and local signal extraction. By adopting an adversarial learning strategy, it enhances the capability to capture semantic information of rPPG under varying resolutions and lighting, bridging the differences in rPPG signal generation due to resolution changes. While maintaining accuracy in HR measuring, the robustness of the network is improved to achieve robust measurement of HR via rPPG. Even under high-resolution conditions, the Mean Absolute Error (MAE) for the three public datasets - unchanging lighting (COHFACE, UBFC-rPPG) and varying lighting (BUAA-MIHR) - reached 1.10 bpm, 1.64 bpm, and 4.41 bpm, respectively, with a mere 0.29 bpm difference in MAE between high and low resolutions on the BUAA-MIHR dataset. This demonstrates that HLFF-AL can predict more robust rPPG signals in various resolutions and lighting scenarios, achieving competitive results compared to state-of-the-art methods. © 1991-2012 IEEE.

关键词： Heart

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Hi-End-MAE: Hierarchical encoder-driven masked autoencoders are stronger vision learners for medical image segmentation

arXiv

引用

arXiv 2025年

作者： Tang, Fenghe Yao, Qingsong Ma, Wenxin Wu, Chenxu Jiang, Zihang Zhou, S. Kevin Anhui Hefei230026 China Suzhou Institute for Advanced Research USTC Suzhou215123 China Stanford University Palo AltoCA94305 United States State Key Laboratory of Precision and Intelligent Chemistry USTC Anhui Hefei230026 China Institute of Computing Technology CAS Beijing100190 China

Medical image segmentation remains a formidable challenge due to the label scarcity. Pre-training Vision Transformer (ViT) through masked image modeling (MIM) on large-scale unlabeled medical datasets presents a promising solution, providing both computational efficiency and model generalization for various downstream tasks. However, current ViT-based MIM pre-training frameworks predominantly emphasize local aggregation representations in output layers and fail to exploit the rich representations across different ViT layers that better capture fine-grained semantic information needed for more precise medical downstream tasks. To fill the above gap, we hereby present Hierarchical Encoder-driven MAE (Hi-End-MAE), a simple yet effective ViT-based pre-training solution, which centers on two key innovations: (1) Encoder-driven reconstruction, which encourages the encoder to learn more informative features to guide the reconstruction of masked patches;and (2) Hierarchical dense decoding, which implements a hierarchical decoding structure to capture rich representations across different layers. We pre-train Hi-End-MAE on a large-scale dataset of 10K CT scans and evaluated its performance across seven public medical image segmentation benchmarks. Extensive experiments demonstrate that Hi-End-MAE achieves superior transfer learning capabilities across various downstream tasks, revealing the potential of ViT in medical imaging applications. The code is available at: https://***/FengheTan9/Hi-End-MAE. Copyright © 2025, The Authors. All rights reserved.

关键词： Computerized tomography

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Logistics Demand Forecasting and Scheduling Optimization Using K-Means Clustering and Deep Q-Network

Logistics Demand Forecasting and Scheduling Optimization Usi...

引用

Electronics, Energy Systems and Power Engineering (EESPE), IEEE International Conference on

作者： Kun Liang Hang Zhang School of Management Tianjin University of Technology Tianjin China Tianjin Key Laboratory for Advanced Mechatronic System Design and Intelligent Control School of Mechanical Engineering Tianjin University of Technology Tianjin China National Demonstration Center for Experimental Mechanical and Electrical Engineering Education Tianjin University of Technology Tianjin China

ISBN: (数字)9798350389579

ISBN: (纸本)9798350389586

With the rapid development of e-commerce and supply chain management, logistics demand forecasting and scheduling optimization have become key links in improving logistics efficiency and service quality. To meet this challenge, this paper proposes a logistics demand forecasting and scheduling optimization method that combines K-Means clustering with deep Q network (DQN). Cluster analysis is used to reduce data complexity, and deep reinforcement learning is used to achieve intelligent scheduling. First, the background, challenges and research motivation of logistics demand forecasting and scheduling optimization are introduced. Secondly, the research results in related fields are reviewed, and the shortcomings of current research are pointed out. Then, the K-Means clustering algorithm, deep $\mathbf{Q}$ network theory and specific models of logistics demand prediction and scheduling optimization are elaborated. Then, the performance of the proposed method is designed and tested. The experimental results show that the proposed method can significantly improve the accuracy of logistics demand prediction, up to 0.93, optimize scheduling strategies, reduce logistics costs, and improve customer satisfaction.

关键词： Training Accuracy Costs Computational modeling Customer satisfaction Demand forecasting Clustering algorithms Predictive models Scheduling Logistics

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